As a result of the digitalization of industrial processes, huge amounts of data are generated in organizations every second. Developing solutions that properly represent this data is critical for making it useful to the organization's stakeholders. Data visualization is a field within computer science that can be utilized to address this demand by enabling the development of appropriate methods for showing the data output of Digital Twins of the Organization (DTO). A recently proposed architecture for a resilient DTO using the EA Blueprint Pattern provides a promising basis for implementing DTOs that are capable of evolving alongside a dynamic organization. However, there is a lack of implementation of any prototypes of the proposed architecture's Information Architecture, which is responsible for dealing with data and visualizing them. Therefore, this thesis aims to develop a visualization prototype, aligned with the proposed architecture. The thesis achieves this goal by first establishing a theoretical basis in data visualization and applicable visualization techniques through a brief review of research articles. After a systematic selection process of visualization tools, the Python frameworks Plotly and Dash are chosen for designing and implementing a visualization prototype. The final design consists of a Python application containing various features and implementing multiple classes which make the prototype easily modifiable and thus able to evolve. In an industrial use case, the prototype is demonstrated to be fulfilling its requirements. Using the observations from the use case, it is finally concluded that the prototype is, in fact, sufficiently aligned with the proposed DTO architecture.